ReviewSensors (Basel, Switzerland)2018
Road Surface Monitoring Using Smartphone Sensors: A Review.
Review in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Automated Road Defect and Anomaly Detection for Traffic Safety: A Systematic Review.Sensors (Basel, Switzerland) · 2023Pooled it
- Road Condition Monitoring Using Smart Sensing and Artificial Intelligence: A Review.Sensors (Basel, Switzerland) · 2022Pooled it
- Road Surface Condition Evaluation Using Imaging, LiDAR, and Multi-Grade Navigation Systems.Sensors (Basel, Switzerland) · 2026Article
- Harnessing Smartphone Sensors for Enhanced Road Safety: A Comprehensive Dataset and Review.Scientific data · 2025Article
- A Vibration-Based Methodology to Monitor Road Surface: A Process to Overcome the Speed Effect.Sensors (Basel, Switzerland) · 2024Article
- Application of Precision Technologies to Characterize Animal Behavior: A Review.Animals : an open access journal from MDPI · 2024Review
- Detection of Road Potholes by Applying Convolutional Neural Network Method Based on Road Vibration Data.Sensors (Basel, Switzerland) · 2023Article
- Evaluating Collaborative and Autonomous Agents in Data-Stream-Supported Coordination of Mobile Crowdsourcing.Sensors (Basel, Switzerland) · 2023Article
- An Improved Deep Neural Network Model of Intelligent Vehicle Dynamics via Linear Decreasing Weight Particle Swarm and Invasive Weed Optimization Algorithms.Sensors (Basel, Switzerland) · 2022Article
- Scanning of Bridge Surface Roughness from Two-Axle Vehicle Response by EKF-UI and Contact Residual: Theoretical Study.Sensors (Basel, Switzerland) · 2022Article
- Smartphone Sensing of Road Surface Condition and Defect Detection.Sensors (Basel, Switzerland) · 2021Article
- On the Application of Time Frequency Convolutional Neural Networks to Road Anomalies' Identification with Accelerometers and Gyroscopes.Sensors (Basel, Switzerland) · 2020Article
- An Automated Machine-Learning Approach for Road Pothole Detection Using Smartphone Sensor Data.Sensors (Basel, Switzerland) · 2020Article
- Inverse Filtering for Frequency Identification of Bridges Using Smartphones in Passing Vehicles: Fundamental Developments and Laboratory Verifications.Sensors (Basel, Switzerland) · 2020Article
- Accuracy Enhancement of Anomaly Localization with Participatory Sensing Vehicles.Sensors (Basel, Switzerland) · 2020Article
- Precise Point Positioning Using World's First Dual-Frequency GPS/GALILEO Smartphone.Sensors (Basel, Switzerland) · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Road surface monitoring is a key factor to providing smooth and safe road infrastructure to road users. The key to road surface condition monitoring is to detect road surface anomalies, such as potholes, cracks, and bumps, which affect driving comfort and on-road safety. Road surface anomaly detection is a widely studied problem. Recently, smartphone-based sensing has become increasingly popular with the increased amount of available embedded smartphone sensors. Using smartphones to detect road surface anomalies could change the way government agencies monitor and plan for road maintenance. However, current smartphone sensors operate at a low frequency, and undersampled sensor signals cause low detection accuracy. In this study, current approaches for using smartphones for road surface anomaly detection are reviewed and compared. In addition, further opportunities for research using smartphones in road surface anomaly detection are highlighted.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.